Introduction to Bioinformatics

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Introduction to Bioinformatics

• Lecture 6
• Substitution matrices

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Sequence Analysis Finding relationships between
genes and gene products of different species,
including those at large evolutionary distances
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Archaea
Domain Archaea is mostly composed of cells that
live in extreme environments. While they are able
to live elsewhere, they are usually not found
there because outside of extreme environments
they are competitively excluded by other
organisms. Species of the domain Archaea are not
inhibited by antibiotics, lack peptidoglycan in
their cell wall (unlike bacteria, which have this
sugar/polypeptide compound), and can have
branched carbon chains in their membrane lipids
of the phospholipid bilayer. It is believed
that Archaea are very similar to prokaryotes that
inhabited the earth billions of years ago. It is
also believed that eukaryotes evolved from
Archaea, because they share many mRNA sequences,
have similar RNA polymerases, and have introns.
Therefore, it is believed that the domains
Archaea and Bacteria branched from each other
very early in history, and membrane infolding
produced eukaryotic cells in the archaean branch
approximately 1.7 billion years ago. There are
three main groups of Archaea extreme halophiles
(salt), methanogens (methane producing
anaerobes), and hyperthermophiles (e.g. living at
temperatures gt100º C!).
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The 20 common amino acids
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Example of sequence database entry for Genbank
LOCUS DRODPPC 4001 bp INV 15-MAR-1990 DEFINITION
D.melanogaster decapentaplegic gene complex
(DPP-C), complete cds. ACCESSION M30116 KEYWORDS .
SOURCE D.melanogaster, cDNA to
mRNA. ORGANISM Drosophila melanogaster Eurkaryo
te mitochondrial eukaryotes Metazoa
Arthropoda Tracheata Insecta Pterygota
Diptera Brachycera Muscomorpha Ephydroidea
Drosophilidae Drosophilia. REFERENCE 1 (bases 1
to 4001) AUTHORS Padgett, R.W., St Johnston,
R.D. and Gelbart, W.M. TITLE A transcript from a
Drosophila pattern gene predicts a
protein homologous to the transforming growth
factor-beta family JOURNAL Nature 325, 81-84
(1987) MEDLINE 87090408 COMMENT The initiation
codon could be at either 1188-1190 or
1587-1589 FEATURES Location/Qualifiers source 1
..4001 /organismDrosophila
melanogaster /db_xreftaxon7227 mRNA lt1..
3918 /genedpp /notedecapentaplegic
protein mRNA /db_xrefFlyBaseFBgn0000490 g
ene 1..4001 /notedecapentaplegic /gene
dpp /allele /db_xrefFlyBaseFBgn000049
0 CDS 1188..2954 /genedpp /notedecap
entaplegic protein (1188 could be
1587) /codon_start1 /db_xrefFlyBaseFBgn
0000490 /db_xrefPIDg157292 /translation
MRAWLLLLAVLATFQTIVRVASTEDISQRFIAAIAPVAAHIPLA
SASGSGSGRSGSRSVGASTSTALAKAFNPFSEPASFSDSDKSHRSKTNKK
PSKSDANR LGYDAYYCHGKCPFPLADHFNSTNAV
VQTLVNNMNPGKVPKACCVPTQLDSVAMLYL NDQSTBVVLKNYQEM
TBBGCGCR BASE COUNT 1170 a 1078 c 956 g 797
t ORIGIN 1 gtcgttcaac agcgctgatc gagtttaaat
ctataccgaa atgagcggcg gaaagtgagc 61
cacttggcgt gaacccaaag ctttcgagga aaattctcgg
acccccatat acaaatatcg 121 gaaaaagtat
cgaacagttt cgcgacgcga agcgttaaga tcgcccaaag
atctccgtgc 181 ggaaacaaag aaattgaggc
actattaaga gattgttgtt gtgcgcgagt gtgtgtcttc
241 agctgggtgt gtggaatgtc aactgacggg ttgtaaaggg
aaaccctgaa atccgaacgg 301 ccagccaaag
caaataaagc tgtgaatacg aattaagtac aacaaacagt
tactgaaaca 361 gatacagatt cggattcgaa
tagagaaaca gatactggag atgcccccag aaacaattca
421 attgcaaata tagtgcgttg cgcgagtgcc agtggaaaaa
tatgtggatt acctgcgaac 481 cgtccgccca
aggagccgcc gggtgacagg tgtatccccc aggataccaa
cccgagccca 541 gaccgagatc cacatccaga
tcccgaccgc agggtgccag tgtgtcatgt gccgcggcat
601 accgaccgca gccacatcta ccgaccaggt gcgcctcgaa
tgcggcaaca caattttcaa . 3841
aactgtataa acaaaacgta tgccctataa atatatgaat
aactatctac atcgttatgc 3901 gttctaagct
aagctcgaat aaatccgtac acgttaatta atctagaatc
gtaagaccta 3961 acgcgtaagc tcagcatgtt
ggataaatta atagaaacga g //
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Example of sequence database entry for SWISS-PROT
(now UNIPROT)
ID DECA_DROME STANDARD PRT 588AA. AC P07713 DT
01-APR-1988 (REL. 07, CREATED) DT 01-APR-1988
(REL. 07, LAST SEQUENCE UPDATE) DT 01-FEB-1995
(REL. 31, LAST ANNOTATION UPDATE) DE DECAPENTAPLEG
IC PROTEIN PRECURSOR (DPP-C PROTEIN). GN DPP. OS D
ROSOPHILA MELANOGASTER (FRUIT FLY). OC EUKARYOTA
METAZOA ARTHROPODA INSECTA DIPTERA. RN 1 RP S
EQUENCE FROM N.A. RM 87090408 RA PADGETT R.W., ST
JOHNSTON R.D., GELBART W.M. RL NATURE 32581-84
(1987) RN 2 RP CHARACTERIZATION, AND SEQUENCE
OF 457-476. RM 90258853 RA PANGANIBAN G.E.F.,
RASHKA K.E., NEITZEL M.D., HOFFMANN F.M. RL MOL.
CELL. BIOL. 102669-2677(1990). CC -!- FUNCTION
DPP IS REQUIRED FOR THE PROPER DEVELOPMENT OF
THE CC EMBRYONIC DOORSAL HYPODERM, FOR
VIABILITY OF LARVAE AND FOR CELL CC VIABILITY
OF THE EPITHELIAL CELLS IN THE IMAGINAL
DISKS. CC -!- SUBUNIT HOMODIMER,
DISULFIDE-LINKED. CC -!- SIMILARITY TO OTHER
GROWTH FACTORS OF THE TGF-BETA FAMILY. DR EMBL
M30116 DMDPPC. DR PIR A26158 A26158. DR HSSP
P08112 1TFG. DR FLYBASE FBGN0000490
DPP. DR PROSITE PS00250 TGF_BETA. KW GROWTH
FACTOR DIFFERENTIATION SIGNAL. FT SIGNAL 1 ? POT
ENTIAL. FT PROPEP ? 456 FT CHAIN 457 588 DECAPENT
APLEGIC PROTEIN. FT DISULFID 487 553 BY
SIMILARITY. FT DISULFID 516 585 BY
SIMILARITY. FT DISULFID 520 587 BY
SIMILARITY. FT DISULFID 552 552 INTERCHAIN (BY
SIMILARITY). FT CARBOHYD 120 120 POTENTIAL. FT CAR
BOHYD 342 342 POTENTIAL. FT CARBOHYD 377 377 POTEN
TIAL. FT CARBOHYD 529 529 POTENTIAL. SQ SEQUENCE
588 AA 65850MW 1768420 CN MRAWLLLLAV
LATFQTIVRV ASTEDISQRF IAAIAPVAAH IPLASASGSG
SGRSGSRSVG ASTSTAGAKA FNRFSEPASF SDSDKSHRSK
TNKKPSKSDA NRQFNEVHKP RTDQLENSKN KSKQLVNKPN
HNKMAVKEQR SHHKKSHHHR SHQPKQASAS TESHQSSSIE
SIFVEEPTLV LDREVASINV PANAKAIIAE QGPSTYSKEA
LIKDKLKPDP STYLVEIKSL LSLFNMKRPP KIDRSKIIIP
EPMKKLYAEI MGHELDSVNI PKPGLLTKSA NTVRSFTHKD
SKIDDRFPHH HRFRLHFDVK SIPADEKLKA AELQLTRDAL
SQQVVASRSS ANRTRYQBLV YDITRVGVRG QREPSYLLLD
TKTBRLNSTD TVSLDVQPAV DRWLASPQRN YGLLVEVRTV
RSLKPAPHHH VRLRRSADEA HERWQHKQPL LFTYTDDGRH
DARSIRDVSG GEGGGKGGRN KRHARRPTRR KNHDDTCRRH
SLYVDFSDVG WDDWIVAPLG YDAYYCHGKC PFPLADHRNS
TNHAVVQTLV NNMNPGKBPK ACCBPTQLDS VAMLYLNDQS
TVVLKNYQEM TVVGCGCR
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What to align, nucleotide or amino acid sequences?

• If ORF then align at protein level
• (i) Many mutations within DNA are synonymous,
  leading to overestimation of sequence divergence
  if compared at the DNA level.
• (ii) Evolutionary relationships can be more
  finely expressed using a 2020 amino acid
  exchange table than using nucleotide exchanges.
• (iii) DNA sequences contain non-coding regions
  which should be avoided in homology searches.
  Still an issue when translating into (six)
  protein sequences through a codon table.
• (iv) Searching at protein level frameshifts can
  occur, leading to stretches of incorrect amino
  acids and possibly elongation of sequences due to
  missed stop codons. But frameshifts normally
  result in stretches of highly unlikely amino
  acids can be used as a signal to trace.

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A 2 R -2 6 N 0 0 2 D 0 -1 2 4 C -2 -4 -4
-5 12 Q 0 1 1 2 -5 4 E 0 -1 1 3 -5 2
4 G 1 -3 0 1 -3 -1 0 5 H -1 2 2 1 -3 3
1 -2 6 I -1 -2 -2 -2 -2 -2 -2 -3 -2 5 L -2 -3
-3 -4 -6 -2 -3 -4 -2 2 6 K -1 3 1 0 -5 1 0
-2 0 -2 -3 5 M -1 0 -2 -3 -5 -1 -2 -3 -2 2 4
0 6 F -4 -4 -4 -6 -4 -5 -5 -5 -2 1 2 -5 0
9 P 1 0 -1 -1 -3 0 -1 -1 0 -2 -3 -1 -2 -5
6 S 1 0 1 0 0 -1 0 1 -1 -1 -3 0 -2 -3 1
2 T 1 -1 0 0 -2 -1 0 0 -1 0 -2 0 -1 -3 0
1 3 W -6 2 -4 -7 -8 -5 -7 -7 -3 -5 -2 -3 -4 0
-6 -2 -5 17 Y -3 -4 -2 -4 0 -4 -4 -5 0 -1 -1 -4
-2 7 -5 -3 -3 0 10 V 0 -2 -2 -2 -2 -2 -2 -1 -2
4 2 -2 2 -1 -1 -1 0 -6 -2 4 B 0 -1 2 3 -4
1 2 0 1 -2 -3 1 -2 -5 -1 0 0 -5 -3 -2 2 Z
0 0 1 3 -5 3 3 -1 2 -2 -3 0 -2 -5 0 0
-1 -6 -4 -2 2 3 A R N D C Q E G H I
L K M F P S T W Y V B Z
PAM250 matrix
WR exchange is too large (due to paucity of data)
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PAM model

• The scores derived through the PAM model are an
  accurate description of the information content
  (or the relative entropy) of an alignment
  (Altschul, 1991).
• PAM-1 corresponds to about 1 million years of
  evolution
• PAM-120 has the largest information content of
  the PAM matrix series
• PAM-250 is the traditionally most popular matrix

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• PAM / MDM / Dayhoff -- summary
• The late Margaret Dayhoff was a pioneer in
  protein databasing and comparison. She and her
  coworkers developed a model of protein evolution
  which resulted in the development of a set of
  widely used substitution matrices. These are
  frequently called Dayhoff, MDM (Mutation Data
  Matrix), or PAM (Percent Accepted Mutation)
  matrices
• Derived from global alignments of closely related
  sequences.
• Matrices for greater evolutionary distances are
  extrapolated from those for lesser ones.
• The number with the matrix (PAM40, PAM100) refers
  to the evolutionary distance greater numbers are
  greater distances.
• Several later groups have attempted to extend
  Dayhoff's methodology or re-apply her analysis
  using later databases with more examples.
• Extensions
• Jones, Thornton and coworkers used the same
  methodology as Dayhoff but with modern databases
  (CABIOS 8275)
• Gonnett and coworkers (Science 2561443 - 1992)
  used a slightly different (but theoretically
  equivalent) methodology
• Henikoff Henikoff (Proteins 1749 - 1993)
  compared these two newer versions of the PAM
  matrices with Dayhoff's originals.

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The Blocks Database The Blocks Database contains
multiple alignments of conserved regions in
protein families. Blocks are multiply aligned
ungapped segments corresponding to the most
highly conserved regions of proteins. The
blocks for the BLOCKS database are made
automatically by looking for the most highly
conserved regions in groups of proteins
represented in the PROSITE database . These
blocks are then calibrated against the SWISS-PROT
database to obtain a measure of the chance
distribution of matches. It is these calibrated
blocks that make up the BLOCKS database. The
database can be searched by e-mail and World Wide
Web (WWW) servers (http//blocks.fhcrc.org/help)
to classify protein and nucleotide sequences.
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The Blocks Database
Gapless alignment blocks
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The BLOSUM series The BLOSUM series of matrices
were created by Steve Henikoff and colleagues
(PNAS 8910915). Derived from local, ungapped
alignments of distantly related sequences All
matrices are directly calculated no
extrapolations are used The number after the
matrix (BLOSUM62) refers to the minimum percent
identity of the blocks used to construct the
matrix greater numbers denote lesser
evolutionary distances. The BLOSUM series of
matrices generally perform better than PAM
matrices for local similarity searches (Proteins
1749).
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The BLOSUM series Blosum30, 35, 40, 45, 50, 55,
60, 62, 65, 70, 75, 80, 85, 90 Blosum62 is based
only on blocks in the BLOCKS database with at
least 62 identity No extrapolations are made in
going to higher evolutionary distancesHigh
blosum - closely related sequencesLow blosum -
distant sequencesblosum62 is the most popular
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BLOSUM62 Matrix, log-odds representation
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Comparing exchange matrices
To compare amino acid exchange matrices, the
"Entropy" value can be used. This is a relative
entropy value which describes the amount of
information available per aligned residue pair.
As two protein sequences diverge over time,
information about the evolutionary process at
work is lost (e.g. back mutations). Therefore,
matrices with larger entropy values are more
sensitive to less divergent sequences, while
matrices with smaller entropy values are more
sensitive to distantly related sequences.
 
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GONNET MatrixA different method to measure
differences among amino acids was developed by
Gonnet, Cohen and Benner (1992) using exhaustive
(i.e. all against all) pairwise alignments of the
protein databases as they existed at that time.
They used classical distance measures to
estimate an alignment of the proteins. They
then used this data to estimate a new distance
matrix. This was used to refine the alignment,
estimate a new distance matrix and so on
iteratively. They noted that the distance
matrices (all first normalized to 250 PAMs)
differed depending on whether they were derived
from distantly or closely homologous proteins.
They suggest that for initial comparisons their
resulting matrix should be used in preference to
a PAM250 matrix, and that subsequent refinements
should be done using a PAM matrix appropriate to
the distance between proteins.
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GONNET Matrix
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Specialized Matrices Claverie (J.Mol.Biol
2341140) has developed a set of substitution
matrices designed explicitly for finding possible
frameshifts in protein sequences. These
matrices are designed solely for use in
protein-protein comparisons they should not be
used with programs which blindly translate DNA
(e.g. 6-frame translation, as is done by the
methods BLASTX or TBLASTN).
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Rissler et al (1988), Overington et al
(1992) Rather than starting from alignments
generated by sequence comparison, Rissler et al
(1988) and later Overington et al (1992) only
considered proteins for which an experimentally
determined three dimensional structure is
available. They then aligned similar proteins on
the basis of their structure rather than sequence
and used the resulting sequence alignments as
their database from which to gather substitution
statistics. In principle, the Rissler or
Overington matrices should give more reliable
results than either PAM of BLOSUM. However, the
comparatively small number of available protein
structures (particularly in the Rissler et al
study) limited the reliability of their
statistics. Overington et al (1992) developed
further matrices that consider the local
environment of the amino acids.
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Amino acid exchange matricessummary

• Apart from the PAM and Blosum series, a great
  number of further matrices have been developed
• Matrices have been made based on DNA, protein
  structure, information content, etc.
• For local alignment, Blosum 62 is often superior
  for distant (global) alignments, Blosum50,
  Gonnet, or (still) PAM250 work well
• Remember that gap penalties are always a problem.
  Unlike the matrices themselves, there is no
  formal way to calculate their values -- you can
  follow recommended settings, but these are based
  on trial and error and not on a formal framework.